`Neural Style Transfer' was introduced by Gatys et al. in `A Neural Algorithm of Artistic Style'  [1]} , and represented a departure from contemporary stylization algorithms in two major ways. First, eschewing hand-crafted features in favor of those extracted by convolutional neural network pretrained for image classification (typically VGG [2]}). Second, synthesizing the stylized output by directly optimizing pixels using gradient descent, rather than by stitching together patches of the style image like previous work.
